Agent-based social simulations for health crises response: utilising the everyday digital health perspective.

Abstract

There is increasing recognition of the role that artificial intelligence (AI) systems can play in managing health crises. One such approach, which allows for analysing the potential consequences of different policy interventions is agent-based social simulations (ABSS). Here, the actions and interactions of autonomous agents are modelled to generate virtual societies that can serve as a "testbed" for investigating and comparing different interventions and scenarios. This piece focuses on two key challenges of ABSS in collaborative policy interventions during the COVID-19 pandemic. These were defining valuable scenarios to simulate and the availability of appropriate data. This paper posits that drawing on the research on the "everyday" digital health perspective in designing ABSS before or during health crises, can overcome aspects of these challenges. The focus on digital health interventions reflects a rapid shift in the adoption of such technologies during and after the COVID-19 pandemic, and the new challenges this poses for policy makers. It is argued that by accounting for the everyday digital health in modelling, ABSS would be a more powerful tool in future health crisis management.